Abstract: A method for an automated video generation from a set of digital images includes the step of obtaining the set of digital images. The set of digital images represent a specified object to be showcased in an automatically generated video. The method includes the step of implementing pose identification on each view of the specified object in the set of digital images. The method includes the step of implementing a background removal operation to set a consistent background to each digital image. The method includes the step of implementing an image resolution increase operation on each digital image. The method includes the step of implementing an attribute extraction operation on each digital image using a set of image classifiers. The set of image classifiers are run on each digital image to generate one or more textual tags. The one or more textual tags are integrated in the automatically generated video; The method includes the step of implementing an attention map generation.

Abstract: In one aspect, a computerized method of computer vision based dynamic universal fashion ontology fashion rating and recommendations includes the step of receiving one or more user-uploaded digital images. The method includes the step of implementing an image classifier on the one or more user-uploaded digital images, to classify a set of user-uploaded fashion content of the one or more user-upload digital images. The method includes the step of receiving a set of fashion rules input by a domain expert. The set of rules determine a set of apparel to match with the set of user-uploaded fashion content, generating a dynamic universal fashion ontology with the image classier and a text classier. The dynamic universal fashion ontology comprises an ontology of set of mutually exclusive attribute classes. The method includes the step of using the dynamic universal fashion ontology to train a specified machine learning based fashion classifications.

Abstract: In one aspect, a computerized method of computer vision based dynamic universal fashion ontology fashion rating and recommendations includes the step of receiving one or more user-uploaded digital images. The method includes the step of implementing an image classifier on the one or more user-uploaded digital images, to classify a set of user-uploaded fashion content of the one or more user-upload digital images. The method includes the step of receiving a set of fashion rules input by a domain expert. The set of rules determine a set of apparel to match with the set of user-uploaded fashion content, generating a dynamic universal fashion ontology with the image classier and a text classier. The dynamic universal fashion ontology comprises an ontology of set of mutually exclusive attribute classes. The method includes the step of using the dynamic universal fashion ontology to train a specified machine learning based fashion classifications.

Abstract: A computer implemented system and method for management of advertisements is disclosed. The system provides effective and efficient management of advertisements. The system provides for effective collaboration of online advertisements and offline advertisements. The system collects advertisements from online resources as well as offline resources, and subsequently converts offline advertisements into online advertisements based on image processing techniques. Further, the system generates advertisements which encompass an optimum fit into the target website, subsequent to analyzing the layout of the target website to identify the advertisements that best suit the target website.

Abstract: A computer implemented system and method for management of advertisements is disclosed. The system provides effective and efficient management of advertisements. The system provides for effective collaboration of online advertisements and offline advertisements. The system collects advertisements from online resources as well as offline resources, and subsequently converts offline advertisements into online advertisements based on image processing techniques. Further, the system generates advertisements which encompass an optimum fit into the target website, subsequent to analyzing the layout of the target website to identify the advertisements that best suit the target website.